On the Compatibility of Fuzzy Control and Conventional Control Techniques
Rainer Palm · 1996
Fuzzy control can be divided into two groups with respect to two main aspects: the first group deals with pure fuzzy systems in which both the signals and the model of the system to be controlled are described by fuzzy sets and respective relations. Most applications, however, use system descriptions based on crisp models, e.g. differential equations, with a nonlinear control element (the fuzzy controller). With this point of view the question arose of how to determine stability, performance and robustness of such mixed crisp-fuzzy systems. Very soon one came to the conclusion that conventional linear and nonlinear control theory is able to contribute very much to deal with such mixed or hybrid systems. To solve the problems of stability, performance and robustness for such systems one is forced to create a common basis in which the fuzzy world is compatible to the crisp one. This common basis can be translation of the whole control loop into fuzzy terms. The other approach is to represent the control loop with all its elements, e.g. the fuzzy controller, as pure conventional and crisp systems, respectively. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.